Estimating the benefit of green infrastructure to urban ecosystems: A synthesis and case-study



Alessandro Filazzola

Scott MacIvor - UTSC

Namrata Shrestha - TRCA

Glenn Milner - OCC

library(tidyverse)
library(PRISMAstatement)

Global urbanization continues unabated, with more than 50% of the worlds’ population living in cities. Cities are conventionally viewed as a threat to local biodiversity because natural habitat is replaced with development. However, more recently, there is greater acknowledgement from the public and private sectors that supporting local environments sustains critical ecosystem services, which in turn improves human health and biodiversity conservation. Consequently, urban planning and design has shifted towards green infrastructure (GI), such as green roofs and retention ponds, to increase connections between city and nature in an era of climate change. The contribution of GI to some ecosystem services has been proven (e.g. stormwater management, building cooling), but the contribution to biodiversity conservation remains unspecified. Using a systematic literature review, this project will (i) determine effect estimates that relate different GI types and characteristics to the impacts on natural systems, and (ii) compile relevant data to develop different implementation scenarios GI for Toronto and region. This study will inform natural system planning and improve quantification of GI on urban ecosystems. Findings from this research will have global ramifications that allow city planners to optimize GI implementation for sustainable development and decrease the impacts of cities on natural systems.

Objectives

  1. A meta-analysis of the literature summarizing the effect of green infrastructure on natural systems.
  2. Using Toronto, Ontario as a case study, develop a tool that can communicates the effectiveness of different GI implementation for biodiversity conservation.

Expected Deliverables

  1. A peer-reviewed journal article that is a meta-analysis from objective 1.
  2. A tool or data analysis that projects different scenarios of green infrastructure implementation for the City of Toronto.

Timeline

date task
June 18 Begin meeting with staff and MacIvor lab to set out workplan
June 25 Begin literature review and data extraction
July 2 Aggregate available data for GI analysis in Toronto
July 3 Complete meetings with TRCA staff on relevant considerations for the project
July 9 Determine important parameters for modelling GI in Toronto
August 20 Complete collection and review of relevant articles
September 3 Conduct meta-analysis on available data
September 10 Propose candidate models for quantifying GI effects for natural systems
Sept 24 Model validation and begin writting manuscript
Oct 15 Complete a draft of manuscript and finalize model

Revise list

search1.1 <- read.csv("data/WOS-lit.csv")
search1.2 <- read.csv("data/WoSPart3-July_4_2018.csv")
net.difference <- anti_join(search1.2, search1.1, by = "DOI")
net.difference <- net.difference %>% select(Title, DOI) #to simplify for a look
nrow(net.difference) #count of number of differences from consecutive search
## [1] 182
## 182 papers to be added by including revised terms
## Select those articles and join with other dataset
net.difference <- anti_join(search1.2, search1.1, by = "DOI")

updated.search <- rbind(search1.1, net.difference)

#write.csv(updated.search, "data/WOS-lit.updated.csv")

Adding revised terms from July 3rd meeting added 182 papers Total articles returned = 1,053 (as of July 2018)

## Adding terms for naturalized pond and pollinator garden
search1.2 <- read.csv("data/WOS-lit.updated.csv")
search1.3 <- read.csv("data/WoSPart4-July_11_2018.csv")
net.difference <- anti_join(search1.3, search1.2, by = "DOI")
net.difference <- net.difference %>% select(Title, DOI) #to simplify for a look
nrow(net.difference) #count of number of differences from consecutive search
## [1] 0
## 213 papers to be added by including revised terms
## Select those articles and join with other dataset
net.difference <- anti_join(search1.3, search1.2, by = "DOI")

updated.search <- rbind(search1.2, net.difference)

#write.csv(updated.search, "data/WOS-lit.updated.csv")

Adding revised terms from July 3rd meeting added 213 papers Total articles returned = 1,224 (as of July 2018)

Literature Review - 2. Sort

This steps includes a. checking for duplicating, b. reviewing each instance for relevancy, c. consistently identifying and documenting exclusion criteria. Outcomes include a list of publications to be used for synthesis, a library of pdfs, and a PRISMA report to ensure the worflow is transparent and reproducible. Papers were excluded with the following characteristics:

  • Not emperical study (e.g. review, book chapter)
  • Irrelevant categories (e.g. political science, law, sports tourism, art)
evidence <- read.csv("data/evidence.csv")
### Identify studies that were excluded
excludes <- evidence %>% group_by(reason) %>% count(exclude) %>% filter(reason!="")
ggplot(excludes, aes(x=reason, y=n)) + geom_bar(stat="identity") + coord_flip()

### Proportion excluded
excludes %>% mutate(percent=n/1140*100) %>%  data.frame(.)
##                             reason exclude   n    percent
## 1                      agriculture       n   1  0.0877193
## 2                      agriculture       y  48  4.2105263
## 3      city or greenspace planning       y 100  8.7719298
## 4                civil engineering       y  17  1.4912281
## 5               climate adaptation       y  27  2.3684211
## 6             conceptual framework       y  39  3.4210526
## 7                    ecology study       n   1  0.0877193
## 8                    ecology study       y 194 17.0175439
## 9                        economics       y  31  2.7192982
## 10                          energy       y   4  0.3508772
## 11       food security/agriculture       y   6  0.5263158
## 12                   GI technology       n   1  0.0877193
## 13                   GI technology       y  60  5.2631579
## 14              industrial ecology       y  18  1.5789474
## 15          modelling conservation       y  52  4.5614035
## 16                          policy       y  59  5.1754386
## 17   regulatory/ecosystem services       y 235 20.6140351
## 18                          review       n   1  0.0877193
## 19                          review       y  80  7.0175439
## 20     social impacts/human health       y  98  8.5964912
## 21 urban ecology/human disturbance       y  55  4.8245614
## frequency of study
year.rate <- evidence %>% group_by(Year) %>% summarize(n=length(Year))

ggplot(tail(year.rate,20)) + geom_bar(aes(x=Year, y=n), stat="identity") + ylab("number of published studies") +xlab("year published") +theme(text = element_text(size=16))

Papers processed - Progress

## Completed so far
prog <- sum(evidence$exclude!="")
prog
## [1] 1266
## Remaining
total <- nrow(evidence)
total
## [1] 1266
setTxtProgressBar(txtProgressBar(0,total,  style = 3), prog)
## 
  |                                                                       
  |                                                                 |   0%
  |                                                                       
  |=================================================================| 100%

Initial pass for relevant papers complete.

Description of studies

GI.type <- evidence %>% group_by(GI.type) %>% count(exclude) %>% filter(GI.type!="")
ggplot(GI.type, aes(x=GI.type, y=n)) + geom_bar(stat="identity") + coord_flip()

Representations of relevant GI types found in papers

Prisma report

## total number of papers found
nrow(evidence)
## [1] 1266
## number of papers found outside of WoS
other <- read.csv("data/other.sources.csv")
nrow(other)
## [1] 28
## number of articles excluded
excludes <- evidence %>% filter(exclude=="y")
nrow(excludes)
## [1] 1123
## relevant papers
review <- evidence %>% filter(exclude!="y")
nrow(review)
## [1] 143
## papers for meta
meta <- evidence %>% filter(meta.=="yes")
nrow(meta)
## [1] 117
prisma(found = 1255,
       found_other = 28,
       no_dupes = 1283,
       screened = 1283,
       screen_exclusions = 1140,
       full_text = 143,
       full_text_exclusions = 0,
       qualitative = 143, 
       quantitative = 66,
       width = 800, height = 800)
## Loading required namespace: DiagrammeR

Literature Review - 3. Synthesis

The research questions we are exploring:

  1. What are the patterns of GI studies globally
  2. How does green infrastructure compare to conventional “grey” equivalents (e.g. green roof to conventional roof)?
  3. How does green infrastructure compare to its natural equivalents (e.g. retention ponds )?
  4. What features of green infrastructure can improve the quality of natural systems?

Patterns of GI Studies Globally

require(ggmap)
###  Start with base map of world
mp <- NULL
mapWorld <- borders("world", colour="gray50", fill="gray50") # create a layer of borders
mp <- ggplot() +   mapWorld

## colorblind-friendly palette
cbPalette <- c("#999999", "#E69F00", "#56B4E9", "#009E73", "#F0E442", "#0072B2", "#D55E00", "#CC79A7","#000000")

meta <- read.csv("data//evidence.csv")
meta <- subset(meta, GI.type!="")

## plot points on top
mp <- mp+ geom_point(data=meta , aes(x=lon, y=lat, color=GI.type), size=2) + scale_colour_manual(values=cbPalette)+
    theme(legend.position="bottom", text = element_text(size=20))
mp

## Number of studies extracted from online data
occurdat<-list.files("data//MS.data",pattern=".csv$",full=T)
length(occurdat)
## [1] 78
## 70 Studies found with usable data for synthesis

Frequency of GI types and taxa

meta <- read.csv("data//Master.GI.Datasets.csv")

freq.GI <- meta %>%  filter(Infrastructure!="grey" & Habitat!="Natural") %>% group_by(GI.type, Taxa.simplified) %>% summarize(n=length(unique(Study))) %>%  data.frame(.)

table.GI <- freq.GI %>% spread(Taxa.simplified, n, fill=0)
#write.csv(table.GI, "Table.GI.csv")

Green infrastructure comparison to conventional

## load master datasets
meta <- read.csv("data//Master.GI.Datasets.csv")
## Omit repo 3 because duplicated with study 1305 and remove repo-9 because not equivalent GI comparisons. Removed Repo 3 because compare roof with ground
meta <- meta %>% filter(Study != "repo.3" & Study!="repo.9" & Study!="repo.1") 

## Drop relative abundance because difference = 0 
meta <- meta %>% filter(Estimate!="Relative.Abundance")

## Load packages and functions
library(reshape2)
library(metafor)
source("meta.eval.r") ## Multiple aggregate


## Create Unique identifier column
meta2 <- meta
meta2[,"UniqueSite"] <- paste(meta2$Study, meta2$Taxa.simplified, meta2$GI.compare, meta$Estimate, sep="-")
meta3 <-  meta2 %>% filter(Infrastructure != "natural") %>%  filter()

## Use function to extract summary statistics for comparisons
## meta.eval  arguments are (meta.data, compare, ids , stats)
Infra.compare <- meta.eval(meta3, Infrastructure, UniqueSite, Stat )

## Combine the lists into same dataframe
## Rename Columns in second dataframe
Infra.stat <- Infra.compare[[2]] ## extracted statistics 
names(Infra.stat) <- c("UniqueSite","green_mean","green_sd","grey_mean","grey_sd","green_n","grey_n") ## rename columns to match
Infra.raw <- Infra.compare[[1]] ## calculated statistics from raw values

## Join two dataframes
meta.stat <- rbind(Infra.raw, Infra.stat[, names(Infra.raw)])


meta.ready <- escalc(n1i = grey_n, n2i = green_n, m1i = grey_mean, m2i = green_mean, sd1i = grey_sd, sd2i = green_sd, data = meta.stat, measure = "SMD", append = TRUE)

## separate out the identifiers
siteID <- matrix(unlist(strsplit(meta.ready$UniqueSite,"-")),ncol=4, byrow=TRUE)
siteID <- data.frame(siteID) ## recreate as dataframe
colnames(siteID) <- c("Study","taxa","GI.compare","measure") ## add column names
meta.ready <- cbind(data.frame(meta.ready), siteID)

#random-effects meta-analysis for green infrastructure vs grey
m1 <- rma(yi=yi, vi=vi,  data = meta.ready)
summary(m1) 
## 
## Random-Effects Model (k = 14; tau^2 estimator: REML)
## 
##   logLik  deviance       AIC       BIC      AICc  
## -20.5203   41.0405   45.0405   46.1704   46.2405  
## 
## tau^2 (estimated amount of total heterogeneity): 1.0014 (SE = 0.4687)
## tau (square root of estimated tau^2 value):      1.0007
## I^2 (total heterogeneity / total variability):   89.59%
## H^2 (total variability / sampling variability):  9.60
## 
## Test for Heterogeneity: 
## Q(df = 13) = 85.6492, p-val < .0001
## 
## Model Results:
## 
## estimate      se     zval    pval    ci.lb    ci.ub     
##  -1.1615  0.2929  -3.9650  <.0001  -1.7357  -0.5874  ***
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
#mixed-effects meta-analysis for green infrastructure vs grey
m2 <- rma(yi=yi, vi=vi, mods=~GI.compare-1,  data = meta.ready)
summary(m2) 
## 
## Mixed-Effects Model (k = 14; tau^2 estimator: REML)
## 
##   logLik  deviance       AIC       BIC      AICc  
## -13.8336   27.6673   39.6673   40.8506   81.6673  
## 
## tau^2 (estimated amount of residual heterogeneity):     0.8848 (SE = 0.5147)
## tau (square root of estimated tau^2 value):             0.9407
## I^2 (residual heterogeneity / unaccounted variability): 84.77%
## H^2 (unaccounted variability / sampling variability):   6.56
## 
## Test for Residual Heterogeneity: 
## QE(df = 9) = 39.6901, p-val < .0001
## 
## Test of Moderators (coefficient(s) 1:5): 
## QM(df = 5) = 22.9955, p-val = 0.0003
## 
## Model Results:
## 
##                                     estimate      se     zval    pval
## GI.comparepublic/community gardens   -0.1442  0.9515  -0.1516  0.8795
## GI.compareretention pond             -1.4397  0.6984  -2.0613  0.0393
## GI.compareroadsides                  -3.5728  1.1849  -3.0153  0.0026
## GI.compareroof                       -1.1249  0.4093  -2.7486  0.0060
## GI.comparewall                       -0.8200  0.5690  -1.4411  0.1496
##                                       ci.lb    ci.ub    
## GI.comparepublic/community gardens  -2.0091   1.7206    
## GI.compareretention pond            -2.8087  -0.0708   *
## GI.compareroadsides                 -5.8951  -1.2504  **
## GI.compareroof                      -1.9271  -0.3228  **
## GI.comparewall                      -1.9352   0.2952    
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## Produce a forest plot to determine the effect sizes for each study
forest(m1, slab = meta.stat$UniqueSite)

## Check for publication bias
## The symetrical distriubtion suggests there is no publication bias
funnel(m1)

## Calculate rosenthals Failsafe number
fsn(yi, vi, data=meta.ready)
## 
## Fail-safe N Calculation Using the Rosenthal Approach 
## 
## Observed Significance Level: <.0001 
## Target Significance Level:   0.05 
## 
## Fail-safe N: 522
### plot Forest plot with each subgroup
res.w <- rma(yi=yi, vi=vi,  data = meta.ready,
             subset=(GI.compare=="wall"))
res.r <- rma(yi=yi, vi=vi,  data = meta.ready,
             subset=(GI.compare=="roof"))
res.p <- rma(yi=yi, vi=vi,  data = meta.ready,
             subset=(GI.compare=="retention pond"))
res.rd <- rma(yi=yi, vi=vi,  data = meta.ready,
             subset=(GI.compare=="roadsides"))

# ## generate plot with spaces inbetween
# forest(m1, atransf=exp, cex=0.75, ylim=c(-1, 24),
#        order=order(meta.ready$GI.compare,meta.ready$taxa), rows=c(3:4,7,10:16,19:21),
# #         mlab="RE model for all studies", psize=1, slab= paste(meta.ready$Study, meta.ready$taxa, meta.ready$measure))
# 
# addpoly(res.w, row=18, cex=0.75, atransf=exp, mlab="RE model for green wall")
# addpoly(res.r, row= 9, cex=0.75, atransf=exp, mlab="RE model for green roof")
# addpoly(res.rd, row= 6, cex=0.75, atransf=exp, mlab="RE model for roadsides")
# addpoly(res.p, row= 2, cex=0.75, atransf=exp, mlab="RE model for retention ponds")

Green infrastructure comparison to natural equivalent

## Create Unique identifier column
meta2 <- meta
meta2[,"UniqueSite"] <- paste(meta2$Study,  meta2$Taxa.simplified, meta2$Nat.compare, meta2$Estimate, sep="-")

## Remove comparisons except urban and rural
meta2 <- meta2 %>% filter(Habitat == "urban" | Habitat == "natural") %>%  filter (Nat.compare != "park") %>%  filter(Study != 1156)

## Determine the number of comparisons available 
compare.eval(meta2, Habitat, UniqueSite)
## [1] 20
## Use function to extract summary statistics for comparisons
## meta.eval  arguments are (meta.data, compare, ids , stats)
nat.compare <- meta.eval(meta2, Habitat, UniqueSite, Stat )


## Combine the lists into same dataframe
## Rename Columns in second dataframe
nat.stat <- nat.compare[[2]] ## extracted statistics 
names(nat.stat) <- c("UniqueSite","natural_mean","natural_sd","urban_mean","urban_sd","natural_n","urban_n") ## rename columns to match
nat.raw <- nat.compare[[1]] ## calculated statistics from raw values

## Join two dataframes
meta.stat <- rbind(nat.raw, nat.stat[, names(nat.raw)])

meta.ready <- escalc(n1i = urban_n, n2i = natural_n, m1i = urban_mean, m2i = natural_mean, sd1i = urban_sd, sd2i = natural_sd, data = meta.stat, measure = "SMD", append = TRUE)

## separate out the identifiers
siteID <- matrix(unlist(strsplit(meta.ready$UniqueSite,"-")),ncol=4, byrow=TRUE)
siteID <- data.frame(siteID) ## recreate as dataframe
colnames(siteID) <- c("Study","taxa","GI.type","measure") ## add column names
meta.ready <- cbind(data.frame(meta.ready), siteID)


#random-effects meta-analysis for urban GI vs natural
m1 <- rma(yi, vi, data = meta.ready)
summary(m1) 
## 
## Random-Effects Model (k = 20; tau^2 estimator: REML)
## 
##   logLik  deviance       AIC       BIC      AICc  
## -15.6201   31.2401   35.2401   37.1290   35.9901  
## 
## tau^2 (estimated amount of total heterogeneity): 0.1093 (SE = 0.0646)
## tau (square root of estimated tau^2 value):      0.3305
## I^2 (total heterogeneity / total variability):   61.67%
## H^2 (total variability / sampling variability):  2.61
## 
## Test for Heterogeneity: 
## Q(df = 19) = 50.6457, p-val = 0.0001
## 
## Model Results:
## 
## estimate      se     zval    pval    ci.lb   ci.ub   
##  -0.0746  0.1037  -0.7192  0.4720  -0.2778  0.1286   
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## Natural vs Urban GI
## Produce a forest plot to determine the effect sizes for each study
forest(m1, slab = meta.stat$UniqueSite, order=order(meta.ready$GI.type,meta.ready$taxa))

## Check for publication bias
## The symetrical distriubtion suggests there is no publication bias
funnel(m1)

#mixed-effects meta-analysis for green infrastructure vs grey
m2 <- rma(yi=yi, vi=vi, mods=~GI.type-1,  data = meta.ready)
summary(m2) 
## 
## Mixed-Effects Model (k = 20; tau^2 estimator: REML)
## 
##   logLik  deviance       AIC       BIC      AICc  
##  -9.3213   18.6425   32.6425   37.1159   51.3092  
## 
## tau^2 (estimated amount of residual heterogeneity):     0.0937 (SE = 0.0692)
## tau (square root of estimated tau^2 value):             0.3062
## I^2 (residual heterogeneity / unaccounted variability): 56.10%
## H^2 (unaccounted variability / sampling variability):   2.28
## 
## Test for Residual Heterogeneity: 
## QE(df = 14) = 35.2094, p-val = 0.0014
## 
## Test of Moderators (coefficient(s) 1:6): 
## QM(df = 6) = 10.7382, p-val = 0.0968
## 
## Model Results:
## 
##                                  estimate      se     zval    pval
## GI.typegreen roof vs. grassland   -0.2744  0.2108  -1.3018  0.1930
## GI.typepond                        0.1140  0.2500   0.4561  0.6483
## GI.typeroadsides vs forest         0.0731  0.2343   0.3121  0.7550
## GI.typeurban garden vs. forest    -0.3060  0.1665  -1.8381  0.0660
## GI.typeurban garden vs. meadow     1.5676  0.8546   1.8344  0.0666
## GI.typewetland vs. bioswale        0.5084  0.3600   1.4122  0.1579
##                                    ci.lb   ci.ub   
## GI.typegreen roof vs. grassland  -0.6875  0.1387   
## GI.typepond                      -0.3760  0.6041   
## GI.typeroadsides vs forest       -0.3861  0.5323   
## GI.typeurban garden vs. forest   -0.6323  0.0203  .
## GI.typeurban garden vs. meadow   -0.1073  3.2425  .
## GI.typewetland vs. bioswale      -0.1972  1.2140   
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## Calculate rosenthals Failsafe number
fsn(yi, vi, data=meta.ready)
## 
## Fail-safe N Calculation Using the Rosenthal Approach 
## 
## Observed Significance Level: 0.1559 
## Target Significance Level:   0.05 
## 
## Fail-safe N: 0

Green infrastructure features in relation to measures of green infrastructure

## The area of green infrastructure
names(meta)[20:21] <- c("GI.area","height")
meta.area <- subset(meta, GI.area>0)

## omit Study 536 & 1304 because raw counts
meta.area <- subset(meta.area, Study != 536 & Study != 1304)

## Determine unique identifier
meta.area[,"UniqueSite"] <- paste(meta.area$Study, meta.area$Taxa.simplified, meta.area$Nat.compare, meta.area$Estimate, sep="-")

## Summarize average richness by area sizes
area.stat <- meta.area %>% filter(Stat=="count" | Stat=="mean") %>% filter(Estimate=="richness") %>%   group_by(Study, GI.area, GI.type) %>% summarize(val=mean(Value)) %>%  data.frame(.)

area.rich <- area.stat %>% filter(GI.type=="green roof" | GI.type=="green wall"  | GI.type=="yards/home gardens" | GI.type=="public/community gardens")

library(ggplot2)

## Species richness per area
ggplot(area.rich,  aes(x=GI.area, y=val, color=GI.type) ) + geom_point(size=3) + theme_bw() + scale_color_brewer(palette="Set2") + ylab("Average species richness") + xlab(expression("Average area of green infrastructure (m"^2*")"))+theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) +  stat_smooth(method="lm", formula= y~poly(x,2),aes(x=GI.area, y=val), color="#181818", fill="#80808080", data=area.rich)

m1 <- lm(val~poly(GI.area,2), data=area.rich)
summary(m1)
## 
## Call:
## lm(formula = val ~ poly(GI.area, 2), data = area.rich)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5.3192 -0.8696 -0.0566  1.0480  7.7911 
## 
## Coefficients:
##                   Estimate Std. Error t value Pr(>|t|)    
## (Intercept)         4.8601     0.1859  26.141  < 2e-16 ***
## poly(GI.area, 2)1   9.9386     1.7929   5.543 2.94e-07 ***
## poly(GI.area, 2)2  -7.1637     1.7929  -3.996 0.000132 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.793 on 90 degrees of freedom
## Multiple R-squared:  0.3416, Adjusted R-squared:  0.3269 
## F-statistic: 23.35 on 2 and 90 DF,  p-value: 6.802e-09
## Summarize average abundance by area sizes
area.stat <- meta.area %>% filter(Stat=="count" | Stat=="mean") %>% filter(Estimate=="abundance") %>%   group_by(Study, GI.area, GI.type) %>% summarize(val=mean(Value)) %>%  data.frame(.)

area.abd <- area.stat %>% filter(GI.type=="green roof" | GI.type=="green wall"  | GI.type=="yards/home gardens" | GI.type=="public/community gardens") %>% 
  filter(GI.area<50000) %>%  ## keep numbers approximately similar - removed outlier of 200,000
filter(Study != 1299 & Study != 1127) 

## Species richness per area
ggplot(area.abd,  aes(x=GI.area, y=val, color=GI.type) ) + geom_point(size=3) + theme_bw() + scale_color_brewer(palette="Set2") + ylab("Average abundance of species") + xlab(expression("Average area of green infrastructure (m"^2*")"))+theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank())

m2 <- lm(val~GI.area, data=area.abd)
summary(m2)
## 
## Call:
## lm(formula = val ~ GI.area, data = area.abd)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -27.825 -21.094   1.306  10.658  82.693 
## 
## Coefficients:
##               Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 27.8430165  2.3709545  11.743   <2e-16 ***
## GI.area     -0.0002494  0.0009327  -0.267     0.79    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 21.85 on 119 degrees of freedom
## Multiple R-squared:  0.0006004,  Adjusted R-squared:  -0.007798 
## F-statistic: 0.07149 on 1 and 119 DF,  p-value: 0.7896
## Compare pH for abundance
ph.data <- meta %>%  filter(pH>0) %>%  filter(GI.type=="retention pond" | GI.type=="natural water")
ph.abd <- ph.data %>% filter(Estimate=="abundance" & Stat=="count")%>%   group_by(pH, GI.type) %>% summarize(val=mean(Value)) %>%  data.frame(.)

## plot richness against pH
ggplot(ph.abd,  aes(x=pH, y=val, color=GI.type) ) + geom_point(size=3) + theme_bw() + scale_color_brewer(palette="Set2") + ylab("Average Richness") + xlab("Average pH of Green Infrastructure")+theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank())

## Compare pH for occurrence
ph.occ <- ph.data %>% filter(Estimate=="occurrence")%>%   group_by(pH, GI.type) %>% summarize(val=mean(Value)) %>%  data.frame(.)

m1 <- glm(Value~ pH, family=binomial, data=ph.data %>% filter(Estimate=="occurrence"))
summary(m1)
## 
## Call:
## glm(formula = Value ~ pH, family = binomial, data = ph.data %>% 
##     filter(Estimate == "occurrence"))
## 
## Deviance Residuals: 
##     Min       1Q   Median       3Q      Max  
## -0.8915  -0.8488  -0.8377   1.5229   1.6131  
## 
## Coefficients:
##             Estimate Std. Error z value Pr(>|z|)
## (Intercept) -0.22413    1.45261  -0.154    0.877
## pH          -0.08643    0.20324  -0.425    0.671
## 
## (Dispersion parameter for binomial family taken to be 1)
## 
##     Null deviance: 308.55  on 251  degrees of freedom
## Residual deviance: 308.37  on 250  degrees of freedom
## AIC: 312.37
## 
## Number of Fisher Scoring iterations: 4
## plot richness against pH
ggplot(ph.occ,  aes(x=pH, y=val, color=GI.type) ) + geom_point(size=3) + theme_bw() + scale_color_brewer(palette="Set2") + ylab("Average Occurrence") + xlab("Average pH of Green Infrastructure")+theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank())

## plot richness against height
h.rich <- meta %>%  filter(height>0)  %>% filter(Estimate=="richness") %>% filter(Stat=="count" | Stat=="mean") %>% group_by(height, GI.type) %>%  summarize(val=mean(Value)) %>%  data.frame(.)

ggplot(h.rich,  aes(x=height, y=val, color=GI.type) ) + geom_point(size=3) + theme_bw() + scale_color_brewer(palette="Set2") + ylab("Average Richness") + xlab("Average Height of Green Infrastructure")+theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank())

## plot abundance against height
h.abd <- meta %>%  filter(height>0)  %>% filter(Estimate=="abundance") %>% filter(Stat=="count" | Stat=="mean") %>% group_by(height, GI.type) %>%  summarize(val=mean(Value)) %>%  data.frame(.)

ggplot(h.abd,  aes(x=height, y=val, color=GI.type) ) + geom_point(size=3) + theme_bw() + scale_color_brewer(palette="Set2") + ylab("Average Abundance") + xlab("Average Height of Green Infrastructure")+theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank())

## Pond salinity
salt <- subset(meta, Salinity>0)
length(unique(salt$Salinity)) ## not enough samples for a meaningful comparison
## [1] 4
## Pond depth
deep <- subset(meta, depth..m.>0)
length(unique(deep$depth..m.)) ## not enough samples for a meaningful comparison
## [1] 4

Case Study - 4. Green infrastructure Mapping

gf.data <- read.csv("data//GI.data//GreenRoofGeocoded.csv")
garden.data <- read.csv("data//GI.data//ComGardensdata.csv")
pond.data <- read.csv("data//GI.data//RetentionPondsGPS.csv")

## Extract coordinates only for GI
gf.data <- gf.data[,c("lon","lat")]
garden.data <- garden.data[,c("lon","lat")]
pond.data <- pond.data[,c("lon","lat")]

## combine into single dataset
GI.data <- rbind(gf.data,garden.data, pond.data)
## add column for data type
GI.data[,"GI.type"] <- c(rep("Green Roof",nrow(gf.data)),rep("Community Garden",nrow(garden.data)),rep("Retention Pond", nrow(pond.data)))

## interactive map
library(leaflet)
## Warning: package 'leaflet' was built under R version 3.4.4
m <- leaflet(data=GI.data) %>%
  addTiles() %>%  
   addCircleMarkers(~lon, ~lat, color =  ifelse(GI.data$GI.type == "Retention Pond", 'blue', 'red'), radius=5)
m

Technical report analyses

meta <- read.csv("data//Master.GI.Datasets.csv")

spp.n <- meta %>% group_by(Genus) %>% summarize(n=length(Species)) %>% arrange(-n) %>% data.frame()
spp.n
##                          Genus     n
## 1                              18277
## 2                      Columba  2338
## 3                       Passer  1843
## 4                       Turdus  1001
## 5                      Vanessa   699
## 6                      Andrena   696
## 7                       Bombus   555
## 8                       Pieris   515
## 9                 Lasioglossum   440
## 10                       Mimus   367
## 11                   Trifolium   351
## 12                   Sturnidae   344
## 13                    Prunella   331
## 14                      Corvus   310
## 15                     Sturnus   257
## 16                      bromus   232
## 17                   polygonum   232
## 18                     Hylaeus   205
## 19                        Rana   202
## 20                      Nomada   199
## 21                   Megachile   192
## 22                   Cracticus   189
## 23                      Cupido   180
## 24                  Locustella   177
## 25                       Osmia   165
## 26                       Parus   164
## 27                    Chaetura   158
## 28                    Halictus   157
## 29                 Anthochaera   139
## 30                     unknown   139
## 31                   Cyanistes   138
## 32                       Larus   138
## 33                       Sedum   132
## 34                   Epipactis   130
## 35                     Senecio   126
## 36                  Asteraceae   124
## 37                   Cheilosia   120
## 38                    Veronica   117
## 39                      bidens   116
## 40                    Harpalus   116
## 41                     ipomoea   116
## 42                   melilotus   116
## 43                      Mirini   116
## 44                    plantago   116
## 45                         poa   116
## 46                  potentilla   116
## 47                    solidago   116
## 48              symphyotrichum   116
## 49                   trifolium   116
## 50                       ulmus   116
## 51                  Ranunculus   115
## 52                        Acer   113
## 53                     Chloris   111
## 54                      Prunus   111
## 55                     Sonchus   111
## 56                     Mutusca   110
## 57               Trichoglossus   109
## 58                      Nysius   107
## 59                      Bellis   106
## 60                   Sphecodes   105
## 61                   Chaetedus   101
## 62                     Solanum   101
## 63                    Manorina   100
## 64                    Geranium    99
## 65                        Rosa    96
## 66                     Schinus    90
## 67                  Spilopelia    90
## 68                        Pica    89
## 69                       Amara    83
## 70                    Grallina    83
## 71                Acridotheres    80
## 72                        Bufo    79
## 73                   Tanacetum    78
## 74                   Euphorbia    77
## 75                      Oxalis    76
## 76                       Vicia    76
## 77                     Primula    74
## 78                      Sorbus    74
## 79                    Eupeodes    73
## 80                         Poa    73
## 81                   Eristalis    72
## 82                Platycherius    72
## 83               Remaudiereana    72
## 84                   Hypericum    70
## 85                   Stellaria    69
## 86                     Cirsium    68
## 87                      Juncus    68
## 88                       Viola    68
## 89                   Cardamine    67
## 90                      Aglais    66
## 91                   Taraxacum    65
## 92                    Lomandra    64
## 93                 Platycercus    64
## 94                   Coelioxys    63
## 95                      Lamium    63
## 96                    Goodenia    62
## 97                    Plantago    62
## 98                    Dianthus    61
## 99                      Galium    60
## 100                Longitarsus    60
## 101                   Medicago    60
## 102                      Nabis    60
## 103                   Ocyphaps    60
## 104               Stenophyella    60
## 105                   acalypha    58
## 106                       acer    58
## 107                  ageratina    58
## 108                  ailanthus    58
## 109                   alliaria    58
## 110                     Allium    58
## 111                 amaranthus    58
## 112                   ambrosia    58
## 113                    arctium    58
## 114                  artemisia    58
## 115                  asclepias    58
## 116                 calystegia    58
## 117                   capsella    58
## 118                    catalpa    58
## 119                  celastrus    58
## 120                     celtis    58
## 121                 chamaesyce    58
## 122                chenopodium    58
## 123                  cichorium    58
## 124                    cirsium    58
## 125                   clematis    58
## 126                  commelina    58
## 127                convolvulus    58
## 128                     conyza    58
## 129                    cynodon    58
## 130                    cyperus    58
## 131                   dactylis    58
## 132                     daucus    58
## 133                  digitaria    58
## 134                  duchesnea    58
## 135                echinochloa    58
## 136                     elymus    58
## 137                   erigeron    58
## 138                   euonymus    58
## 139                    festuca    58
## 140                  galinsoga    58
## 141                   glechoma    58
## 142                     hedera    58
## 143                hypochaeris    58
## 144                    juglans    58
## 145                     juncus    58
## 146                    lactuca    58
## 147                   lepidium    58
## 148                     lolium    58
## 149                   lonicera    58
## 150                      lotus    58
## 151                   medicago    58
## 152               microstegium    58
## 153                      morus    58
## 154                     oxalis    58
## 155             parthenocissus    58
## 156                  paulownia    58
## 157                 phytolacca    58
## 158                   platanus    58
## 159                    quercus    58
## 160                       rosa    58
## 161                      rubus    58
## 162                      rumex    58
## 163                 securigera    58
## 164                    senecio    58
## 165                    setaria    58
## 166                 sisymbrium    58
## 167                    sonchus    58
## 168                  taraxacum    58
## 169              toxicodendron    58
## 170                   veronica    58
## 171                      vicia    58
## 172                      viola    58
## 173                      vitis    58
## 174               Wahlenbergia    58
## 175                   Bursaria    57
## 176                 Eucalyptus    57
## 177                   Raphanus    56
## 178                  Anagallis    55
## 179                  Polygonum    55
## 180                    Hirundo    54
## 181                    Pararge    53
## 182                       Apis    52
## 183                 Rosmarinus    52
## 184                 Calystegia    51
## 185                  Ligustrum    51
## 186                      Rubus    51
## 187                     Salvia    51
## 188                    Spiraea    51
## 189                Convolvulus    50
## 190                Pelargonium    50
## 191                     Sitona    50
## 192                     Acacia    49
## 193                  Lavandula    49
## 194                    Stachys    49
## 195                    Syrphus    49
## 196                Dasysyrphus    48
## 197                    Galenia    48
## 198                 Helophilus    48
## 199                      Malva    48
## 200                Melanostoma    48
## 201                      plant    48
## 202                 Potentilla    48
## 203                     Sidnia    48
## 204                  Volucella    48
## 205                     Xylota    48
## 206                 Cardinalis    47
## 207                  Epilobium    47
## 208                    Festuca    47
## 209                   Capsella    46
## 210                   Myoporum    46
## 211                      Canna    45
## 212                   Colletes    45
## 213                     Mentha    45
## 214                   Ocirrhoe    45
## 215                     Sylvia    45
## 216                     Conyza    44
## 217                    Lapsana    44
## 218               Glossopsitta    43
## 219                  Anthidium    42
## 220                 Chelostoma    42
## 221                   Glechoma    42
## 222                       Hyla    42
## 223                 Limanarium    42
## 224                    Melitta    42
## 225                  Santolina    42
## 226                  Cerastium    41
## 227                  Cuspicona    41
## 228                Lissotriton    41
## 229                  Melaleuca    41
## 230                   Achillea    40
## 231                    Olearia    40
## 232                     Spinus    40
## 233                   Buddleja    39
## 234                      Carex    39
## 235                    Cacatua    38
## 236               Plectranthus    38
## 237                    Zenaida    38
## 238                    Begonia    37
## 239                       Iris    37
## 240                     Lolium    37
## 241                 Agapanthus    36
## 242                Cotoneaster    36
## 243                Leucophaeus    36
## 244                     Nepeta    36
## 245               Orthotylinae    36
## 246                     Picris    36
## 247                Pseudacris     36
## 248                     Silene    36
## 249                   Halticus    35
## 250                      Rumex    35
## 251                 Anthophora    34
## 252                 Bombycilla    34
## 253                   Dactylis    34
## 254                   Fraxinus    34
## 255                 Pardalotus    34
## 256                    Petunia    34
## 257                      Ajuga    33
## 258                   Atriplex    33
## 259                 Lysimachia    33
## 260                 Melissodes    33
## 261                    Tagetes    33
## 262                   Viburnum    33
## 263                  Aquilegia    32
## 264                  Campanula    32
## 265                     Dietes    32
## 266                    Ficinia    32
## 267                     Gahnia    32
## 268                      Gaura    32
## 269                 Haemorhous    32
## 270                      Lotus    32
## 271                    Papaver    32
## 272                      Salix    32
## 273                  Fringilla    31
## 274                  Hieracium    31
## 275                     Atheta    30
## 276                  Centaurea    30
## 277                   Lathyrus    30
## 278                   Lonicera    30
## 279                  Melospiza    30
## 280                   Myosotis    30
## 281                   Phylinae    30
## 282                     Thymus    30
## 283                   Aesculus    29
## 284              Argyranthemum    29
## 285                Chenopodium    29
## 286                     Crepis    29
## 287                   Eolophus    29
## 288                   Heriades    29
## 289               Leucanthemum    29
## 290               Pentatomidae    29
## 291                  Crataegus    28
## 292                      Hosta    28
## 293                    Lychnis    28
## 294                   Ageratum    27
## 295                    Alyssum    27
## 296                    Anemone    27
## 297                 Anthriscus    27
## 298                Chelidonium    27
## 299                     Cornus    27
## 300                  Digitalis    27
## 301                     Lilium    27
## 302                      Ribes    27
## 303                    Syringa    27
## 304                      Tilia    27
## 305                     Urtica    27
## 306                   Alliaria    26
## 307              Anisodactylus    26
## 308                   Berberis    26
## 309               Ceratostigma    26
## 310                Chinoneides    26
## 311                      Malus    26
## 312                    Muscari    26
## 313               Rhododendron    26
## 314                  Symphytum    26
## 315            Trachelospermum    26
## 316                  Acanthiza    25
## 317                  Duchesnea    25
## 318                   Erysimum    25
## 319                    Fuchsia    25
## 320                     Hedera    25
## 321                Helichrysum    25
## 322                     Hypera    25
## 323                     Iberis    25
## 324                       Ilex    25
## 325                   Laburnum    25
## 326                  Leontodon    25
## 327                   Magnolia    25
## 328                  Narcissus    25
## 329                 Philonthus    25
## 330                 Pulmonaria    25
## 331                    Quedius    25
## 332                   Solidago    25
## 333                 Tachyporus    25
## 334           Tripleurospermum    25
## 335                   Agrostis    24
## 336                 Alchemilla    24
## 337                   Aubretia    24
## 338                     Baccha    24
## 339                  Calendula    24
## 340              Chalcosyrphus    24
## 341                   Cheilosa    24
## 342                    Choisya    24
## 343               Chrysogaster    24
## 344                    Circaea    24
## 345                  Claytonia    24
## 346                   Colpodes    24
## 347                    Crompus    24
## 348               Deraeocorini    24
## 349                  Dictyotus    24
## 350                  Dicyphini    24
## 351                   Dilompus    24
## 352                 Epistrophe    24
## 353                 Episyrphus    24
## 354                      Erica    24
## 355                    Eumerus    24
## 356                  Eupolemus    24
## 357                Ferdinandea    24
## 358                       Hebe    24
## 359                   Heringia    24
## 360              Hyacinthoides    24
## 361                      Inula    24
## 362                       Itea    24
## 363                      Large    24
## 364               Liriodendron    24
## 365                 Matricaria    24
## 366                 Meconopsis    24
## 367                  Melangyna    24
## 368               Melanogaster    24
## 369                 Meliscaeva    24
## 370                    Merodon    24
## 371                  Myathropa    24
## 372                   Neoascia    24
## 373                    Nigella    24
## 374                     Orchis    24
## 375                 Oxycarenus    24
## 376                      Pansy    24
## 377                Parasyrphus    24
## 378                  Phygelius    24
## 379                  Pilosella    24
## 380               Platycheirus    24
## 381                 Plinthisus    24
## 382                Polyommatus    24
## 383                 Portevinia    24
## 384              Pseudofumaria    24
## 385                 Rhinanthus    24
## 386                    Rhingia    24
## 387                  Rhipidura    24
## 388                Riponnensia    24
## 389                   Sambucas    24
## 390                     Scaeva    24
## 391                      Small    24
## 392              Sphaerophoria    24
## 393                    Syritta    24
## 394                     Tingis    24
## 395                       Ulex    24
## 396                   Vanellus    24
## 397                     Violet    24
## 398                   Weigelia    24
## 399               Xanthogramma    24
## 400                     Yellow    24
## 401                  Bembidion    23
## 402                  Galinsoga    23
## 403                      Pinus    23
## 404                  Artemisia    22
## 405                   Baptisia    22
## 406                     Correa    22
## 407                Hypochaeris    22
## 408                      Orius    22
## 409                    Verbena    22
## 410                Xerochrysum    22
## 411                     Celtis    21
## 412                    Lythrum    21
## 413                  Aleochara    20
## 414                       Anas    20
## 415                 Eysarcoris    20
## 416                  Mcateella    20
## 417                Phyllotreta    20
## 418                  Protapion    20
## 419                    Amorbus    19
## 420                   Clematis    19
## 421                      Falco    19
## 422                     Nebria    19
## 423                Stephanitis    19
## 424                 Amaranthus    18
## 425                 Baclozygum    18
## 426                Coridromius    18
## 427                   Emesinae    18
## 428              Lagerstraemia    18
## 429                 Megachilie    18
## 430                      Phaps    18
## 431                  Ptilotula    18
## 432               Brentiscerus    17
## 433                  Erythrina    17
## 434                  Grevillea    17
## 435                    Robinia    17
## 436                     Abelia    16
## 437                Brachyscome    16
## 438                   Dindymus    16
## 439                 Ozothamnus    16
## 440                 Parietaria    16
## 441               Pheropsophus    16
## 442                 Sericornis    16
## 443                   Synuchus    16
## 444                   Agriotes    15
## 445                   Atomaria    15
## 446                 Cermatulus    15
## 447             Cryptocephalus    15
## 448                   Cymodema    15
## 449                 Froggattia    15
## 450                    Gabrius    15
## 451                   Gminatus    15
## 452                     Mictis    15
## 453                     Nerium    15
## 454               Platystethus    15
## 455                   Sambucus    15
## 456                     Stenus    15
## 457                    Tychius    15
## 458                   Ceratina    14
## 459                    Certhia    14
## 460                   Corvidae    14
## 461                  Lamiaceae    14
## 462                   Lepidium    14
## 463               Pterostichus    14
## 464                  Rudbeckia    14
## 465                      Ulmus    14
## 466                    Lactuca    13
## 467                    Malurus    13
## 468                    Unknown    13
## 469                Agapostemon    12
## 470               Angiozanthos    12
## 471                   Anischys    12
## 472                   Bauhinia    12
## 473              Buchananiella    12
## 474                     Cletus    12
## 475                    Coranus    12
## 476                Creontiades    12
## 477             Cryptorhamphus    12
## 478                   Dianella    12
## 479                 Dicrotelus    12
## 480                   Dieuches    12
## 481                 Diplocysta    12
## 482                     Echium    12
## 483                   Eribotes    12
## 484                  Eritingis    12
## 485                    Euander    12
## 486                     Eucera    12
## 487                 Eurynysius    12
## 488                    Gelonus    12
## 489                   Germalus    12
## 490                       Geum    12
## 491                Hesperiidae    12
## 492                  Hydrangea    12
## 493               Koscocrompus    12
## 494              Lasioglossum     12
## 495                  Lethaeini    12
## 496                 Malandiola    12
## 497              Melanacanthus    12
## 498                      Melia    12
## 499                     Nezara    12
## 500                     Notius    12
## 501                   Oechalia    12
## 502                  Oncocoris    12
## 503                   Ontiscus    12
## 504                  Penstemon    12
## 505               Pipistrellus    12
## 506                  Portulaca    12
## 507                 Pseudacris    12
## 508                     Stelis    12
## 509              Stizocephalus    12
## 510              Stylogeocoris    12
## 511             Symphyotrichum    12
## 512             Thaumastocoris    12
## 513                   Ulonemia    12
## 514                    Zanessa    12
## 515                     Agonum    11
## 516                  Ailanthus    11
## 517                  Asclepias    11
## 518                     Betula    11
## 519                  Ceratonia    11
## 520                     Colias    11
## 521                    Delonix    11
## 522                Deschampsia    11
## 523                 Eupatorium    11
## 524                     Eurema    11
## 525                    Hordeum    11
## 526                    Kickxia    11
## 527                   Oedemera    11
## 528                       Olea    11
## 529                    Ophonus    11
## 530               Phylloscopus    11
## 531                   Syntomus    11
## 532                    Tamarix    11
## 533                      Thuja    11
## 534                    Agathis    10
## 535                    Amischa    10
## 536                Amphimallon    10
## 537                 Asiorestia    10
## 538               Bignoniaceae    10
## 539                    Bledius    10
## 540               Brachychiton    10
## 541                 Brachypera    10
## 542                Bradycellus    10
## 543                   Calathus    10
## 544                 Carpelimus    10
## 545                     Cedrus    10
## 546              Ceutorhynchus    10
## 547                Chaetocnema    10
## 548               Chlorophytum    10
## 549                Corticarina    10
## 550                Cortinicara    10
## 551                  Cyanapion    10
## 552                  Danthonia    10
## 553                   Diabolia    10
## 554              Dichanthelium    10
## 555                 Elaphropus    10
## 556                    Epuraea    10
## 557                   Galeruca    10
## 558                      Hakea    10
## 559               Harpephyllum    10
## 560             Hemitrichapion    10
## 561                   Ionactis    10
## 562                  Lagunaria    10
## 563                  Lespedeza    10
## 564               Margarinotus    10
## 565             Melanophthalma    10
## 566                   Monotoma    10
## 567                      Morus    10
## 568                       Musa    10
## 569                     Ocypus    10
## 570                Onthophagus    10
## 571                     Othius    10
## 572                    Panicum    10
## 573                   Platanus    10
## 574                Platydracus    10
## 575                  Polygonia    10
## 576              Pseudoophonus    10
## 577                 Psylliodes    10
## 578               Pycnanthemum    10
## 579              Schizachyrium    10
## 580                   Scopaeus    10
## 581                    Searsia    10
## 582                    Sophora    10
## 583                Sorghastrum    10
## 584                    Tasgius    10
## 585                      Trema    10
## 586                Xantholinus    10
## 587                     Bromus     9
## 588                    Melecta     9
## 589                Mercurialis     9
## 590                    Monarda     9
## 591                    Mycelis     9
## 592                  Psephotus     9
## 593                  Angelonia     8
## 594               Anthropodium     8
## 595                    Arctium     8
## 596              Augochlorella     8
## 597              Bougainvillea     8
## 598                  Brachinus     8
## 599                  Chlaenius     8
## 600                     Clivia     8
## 601                  Craspedia     8
## 602                     Daucus     8
## 603                   Dolichus     8
## 604                   Fallopia     8
## 605                 Foeniculum     8
## 606             Haplochlaenius     8
## 607                   Lecanora     8
## 608                   Lesticus     8
## 609                 Megachile      8
## 610                 Persicaria     8
## 611                      Phyla     8
## 612                 Pomaderris     8
## 613                  Verbascum     8
## 614                   Xylocopa     8
## 615                  Accipiter     7
## 616                   Badister     7
## 617                  Caloplaca     7
## 618              Colluricincla     7
## 619                   Coracina     7
## 620                  Digitaria     7
## 621                   Erigeron     7
## 622                   Hylaeus      7
## 623               Phylidonyris     7
## 624                   Poecilus     7
## 625                    Rorippa     7
## 626                 Sisymbrium     7
## 627                    Amorpha     6
## 628                 Augochlora     6
## 629                    Ballota     6
## 630             Chrysoceohalum     6
## 631                      Dalea     6
## 632                Echinochloa     6
## 633                  Elytrigia     6
## 634                   Hoplitis     6
## 635                  Kalanchoe     6
## 636                    Linaria     6
## 637                    Liriope     6
## 638                 Lithobates     6
## 639                   Loricera     6
## 640              Melanocanthus     6
## 641                  Molothrus     6
## 642               Pachycephala     6
## 643                    Pimelea     6
## 644                   Podargus     6
## 645                     Sagina     6
## 646                    Serinus     6
## 647                  Sherardia     6
## 648                    Sinapis     6
## 649                 Strelitzia     6
## 650                   Tingidae     6
## 651                      Zizia     6
## 652                 Ablattaria     5
## 653                   Acrotona     5
## 654                  Acupalpus     5
## 655                   Agrypnus     5
## 656                      Alcea     5
## 657                  Aloconota     5
## 658                     Altica     5
## 659                 Amarochara     5
## 660                   Anacaena     5
## 661                    Anaspis     5
## 662                   Anotylus     5
## 663                   Anthicus     5
## 664                  Anthrenus     5
## 665                  Anthribus     5
## 666                   Aphodius     5
## 667                   Arenaria     5
## 668                   Arpedium     5
## 669                 Arthrolips     5
## 670                    Astenus     5
## 671                   Bacidina     5
## 672                      Baris     5
## 673                     Bitoma     5
## 674                    Bombus      5
## 675              Brachythecium     5
## 676                   Brassica     5
## 677                    Bruchus     5
## 678                    Byrrhus     5
## 679                  Cantharis     5
## 680                  Carduelis     5
## 681                  Cartodere     5
## 682                    Cassida     5
## 683                 Ceratapion     5
## 684                    Cercyon     5
## 685                 Chrysolina     5
## 686                   Cidnopus     5
## 687                        Cis     5
## 688                Clanoptilus     5
## 689                 Coccinella     5
## 690                 Corticaria     5
## 691                   Corymbia     5
## 692               Cryptophagus     5
## 693              Cryptopleurum     5
## 694                  Cteniopus     5
## 695                 Curtimorda     5
## 696                 Cyanocitta     5
## 697                  Cynegetis     5
## 698                    Cytilus     5
## 699                   Dinaraea     5
## 700                Dolichosoma     5
## 701                     Dorcus     5
## 702                     Dryops     5
## 703                    Enicmus     5
## 704                Ennearthron     5
## 705                 Ephistemus     5
## 706                    Erigone     5
## 707                  Eucinetus     5
## 708               Eutrichapion     5
## 709                   Fragaria     5
## 710                Gastrophysa     5
## 711                Gauropterus     5
## 712                  Gymnetron     5
## 713                 Gyrohypnus     5
## 714                    Halyzia     5
## 715                   Harmonia     5
## 716                 Helophorus     5
## 717                   Hibiscus     5
## 718                 Hippodamia     5
## 719               Hirschfeldia     5
## 720                 Hirticomus     5
## 721                      Hispa     5
## 722                     Hister     5
## 723                     Holcus     5
## 724             Holotrichapion     5
## 725                     Hoplia     5
## 726                  Impatiens     5
## 727            Ischnopterapion     5
## 728                 Ischnosoma     5
## 729                  Lionychus     5
## 730                Lithocharis     5
## 731                    Mecinus     5
## 732                Megasternum     5
## 733                Melissodes      5
## 734                   Metopsia     5
## 735                Microlestes     5
## 736                Mycetoporus     5
## 737                Necrophorus     5
## 738                 Neobisnius     5
## 739                     Ocyusa     5
## 740                    Olibrus     5
## 741                    Omalium     5
## 742                   Omonadus     5
## 743                  Orchestes     5
## 744                   Origanum     5
## 745               Otiorhynchus     5
## 746                     Oulema     5
## 747                    Oxyomus     5
## 748                    Oxypoda     5
## 749                   Oxystoma     5
## 750                  Parocyusa     5
## 751                 Parophonus     5
## 752                  Peponapis     5
## 753                   Physalis     5
## 754                 Pityogenes     5
## 755                Plathyrinus     5
## 756                Platynaspis     5
## 757                   Propylea     5
## 758                  Proteinus     5
## 759                 Psammodius     5
## 760                 Psyllobora     5
## 761                    Rabigus     5
## 762                    Rhinusa     5
## 763                  Rhyzobius     5
## 764                  Saponaria     5
## 765               Sepedophilus     5
## 766                    Sibinia     5
## 767                Simplocaria     5
## 768                  Stegobium     5
## 769                  Stelidota     5
## 770                 Stenocarus     5
## 771                Stenolophus     5
## 772             Stenopterapion     5
## 773         Teretriorhynchites     5
## 774              Thanatophilus     5
## 775                   Timarcha     5
## 776                    Tinotus     5
## 777                    Trechus     5
## 778            Trichopterapion     5
## 779            Trichosirocalus     5
## 780                 Triepeolus     5
## 781                    Tritoma     5
## 782                 Tytthaspis     5
## 783                     Valgus     5
## 784                 Variimorda     5
## 785                  Xyleborus     5
## 786                   Zacladus     5
## 787                   Zoosetha     5
## 788                  Zorochros     5
## 789                   Acanthus     4
## 790                Archilochus     4
## 791              Brachychitron     4
## 792               Brachypodium     4
## 793                  Caligavis     4
## 794                   Cassinia     4
## 795                  Cisticola     4
## 796                     Cistus     4
## 797                  Coleonema     4
## 798                  Dumetella     4
## 799                 Eopsaltria     4
## 800                  Equisetum     4
## 801                    Erodium     4
## 802                 Helianthus     4
## 803                   Limanium     4
## 804                    Melissa     4
## 805                    Nandina     4
## 806                Notiophilus     4
## 807                   Nyctalus     4
## 808                  Oenothera     4
## 809                 Pelagonium     4
## 810                 Soleirolia     4
## 811                    Torilis     4
## 812                  Tussilago     4
## 813                 Verrucaria     4
## 814               Walckenaeria     4
## 815            Acanthorhynchus     3
## 816                 Aegithalos     3
## 817                 Aegopodium     3
## 818                   Andrena      3
## 819                Antirrhinum     3
## 820                    Astilbe     3
## 821                   Barbarea     3
## 822                     Borago     3
## 823                Calibrachoa     3
## 824              Candelariella     3
## 825                   Carpinus     3
## 826                  Casuarina     3
## 827                 Centaurium     3
## 828                  Cichorium     3
## 829                   Cladonia     3
## 830                     Cleome     3
## 831                   Colleies     3
## 832                  Coreopsis     3
## 833                  Corydalis     3
## 834                     Cosmos     3
## 835                  Cucurbita     3
## 836                     Dacelo     3
## 837                     Dahlia     3
## 838              Diplocephalus     3
## 839                 Diplotaxis     3
## 840                 Dryopteris     3
## 841                  Echinacea     3
## 842                      Ficus     3
## 843                  Gladiolus     3
## 844                  Halictus      3
## 845               Hemerocallis     3
## 846                  Herniaria     3
## 847                   Heuchera     3
## 848                  Isodontia     3
## 849                  Kniphofia     3
## 850                    Lantana     3
## 851                     Lasius     3
## 852                    Liatris     3
## 853                      Linum     3
## 854                    Lobelia     3
## 855                     Luzula     3
## 856                  Melilotus     3
## 857                   Neochmia     3
## 858                     Ocimum     3
## 859                 Oedothorax     3
## 860                    Papilio     3
## 861                  Perovskia     3
## 862                      Phlox     3
## 863             Pseudopanurgus     3
## 864                    Quercus     3
## 865                     Reseda     3
## 866                 Rondeletia     3
## 867                Schistidium     3
## 868                    Setaria     3
## 869                  Setophaga     3
## 870                Spergularia     3
## 871                   Strepera     3
## 872                    Svastra     3
## 873                      Taxus     3
## 874               Tenuiphantes     3
## 875               Tradescantia     3
## 876                   Trapelia     3
## 877                Troglodytes     3
## 878                    Vespula     3
## 879                      Vinca     3
## 880                    Weigela     3
## 881                  Xanthoria     3
## 882                     Zinnia     3
## 883               Agapostemon      2
## 884                  Agastache     2
## 885                   Amegilla     2
## 886                    Anethum     2
## 887                  Angophora     2
## 888                 Anthidium      2
## 889                Arabidopsis     2
## 890                  Araucaria     2
## 891                 Artocarpus     2
## 892                  Asplenium     2
## 893                 Baeolophus     2
## 894               Bathyphantes     2
## 895                     Bidens     2
## 896                      Bryum     2
## 897                 Calliopsis     2
## 898                   Capsicum     2
## 899                Carpobrotus     2
## 900                 Celastrina     2
## 901                    Celosia     2
## 902                Centromerus     2
## 903                  Ceratina      2
## 904                  chinensis     2
## 905                 Cinnamomum     2
## 906                   Clubiona     2
## 907                  Commelina     2
## 908                 Coriandrum     2
## 909                    Corylus     2
## 910                     Cotula     2
## 911                    Cucumis     2
## 912                   Cyclamen     2
## 913                 Cymbalaria     2
## 914                     Datura     2
## 915                Dendrocopos     2
## 916                Dodecatheon     2
## 917               Enoplognatha     2
## 918                    Epacris     2
## 919                    Epeolus     2
## 920                 Eragrostis     2
## 921                 Eriobotrya     2
## 922                     Falcol     2
## 923                      Gagea     2
## 924                  Galanthus     2
## 925                    Galenis     2
## 926                  Galeopsis     2
## 927                     Hahnia     2
## 928                  Heleborus     2
## 929                  Hippolais     2
## 930               Holcopasites     2
## 931                       Hoya     2
## 932                    Humulus     2
## 933              Hylotelephium     2
## 934                     Hypnum     2
## 935               Ichthyosaura     2
## 936                    Icterus     2
## 937                    Ipomoea     2
## 938                  Jacaranda     2
## 939                   Jasminum     2
## 940                     Lablab     2
## 941                    Lecania     2
## 942                  Lecidella     2
## 943                   Lepraria     2
## 944                   Linyphia     2
## 945                Lipotriches     2
## 946                Lophostemon     2
## 947                   Macropis     2
## 948                     maxima     2
## 949                  Megalurus     2
## 950                   Meioneta     2
## 951                     Melica     2
## 952               Melithreptus     2
## 953                  Nemastoma     2
## 954               Nesoptilotis     2
## 955                   Observed     2
## 956               Orthotrichum     2
## 957                   Ozyptila     2
## 958             Parthenocissus     2
## 959                 Pelophylax     2
## 960              Petrochelidon     2
## 961               Petroselinum     2
## 962               Phaeophyscia     2
## 963                 Philanthus     2
## 964                Phoenicurus     2
## 965                    Phoenix     2
## 966                    Physcia     2
## 967                 Phytolacca     2
## 968              Placynthiella     2
## 969                 Platycodon     2
## 970                   Plumbago     2
## 971                    Populus     2
## 972                  Porrhomma     2
## 973                    Prionyx     2
## 974                   Ratibida     2
## 975                      regia     2
## 976                 Salamandra     2
## 977                Sanguisorba     2
## 978                  Saxifraga     2
## 979                   Scabiosa     2
## 980               Scrophularia     2
## 981                 Securigera     2
## 982                Sempervivum     2
## 983                   Sorbaria     2
## 984                      Sphex     2
## 985                     Spirea     2
## 986                   Spizella     2
## 987                   Steatoda     2
## 988                   Stokesia     2
## 989                     Sutera     2
## 990                   Syzygium     2
## 991                  Tegenaria     2
## 992                    Torenia     2
## 993                    Tortula     2
## 994                 Tragopogon     2
## 995                  Triodanis     2
## 996                   Triturus     2
## 997               Unidentified     2
## 998                  variegata     2
## 999              Veronicastrum     2
## 1000                Vittadinia     2
## 1001                Westringia     2
## 1002              Zantedeschia     2
## 1003                Iphiclides     1
## 1004                  Acarospo     1
## 1005                  Aconitum     1
## 1006                   Aethusa     1
## 1007              Afranthidium     1
## 1008                 Ageratina     1
## 1009                 Agrimonia     1
## 1010                   Agroeca     1
## 1011                      alba     1
## 1012                 Aleurites     1
## 1013                alexandrae     1
## 1014                    Alisma     1
## 1015                  Aloxyria     1
## 1016                 Amandinea     1
## 1017              Amblystegium     1
## 1018                  Ambrosia     1
## 1019               Amelanchier     1
## 1020                 americana     1
## 1021                Anchomenus     1
## 1022             Ancistrocerus     1
## 1023                    Annona     1
## 1024               Anthophora      1
## 1025                 Anyphaena     1
## 1026                     Apera     1
## 1027                     Apis      1
## 1028                  Apocynum     1
## 1029                 Araeoncus     1
## 1030           Archontophoenix     1
## 1031             Arrhenatherum     1
## 1032                Asaphidion     1
## 1033                 Asparagus     1
## 1034                  Asperula     1
## 1035                 Aspicilia     1
## 1036                     Aster     1
## 1037               Augochlora      1
## 1038                     Avena     1
## 1039                 azedarach     1
## 1040                babylonica     1
## 1041                    Ballus     1
## 1042                   Barbula     1
## 1043                    Bembix     1
## 1044                 benjamina     1
## 1045                  Berteroa     1
## 1046                 Bischofia     1
## 1047                    Bombax     1
## 1048        Bryoerythrophyllum     1
## 1049                   Bryonia     1
## 1050                   Buellia     1
## 1051                 burmanii*     1
## 1052                     Buteo     1
## 1053                     Buxus     1
## 1054  cajuputi ssp. Cumingiana     1
## 1055             Calamagrostis     1
## 1056                Calamintha     1
## 1057               Callistemon     1
## 1058                Calophasia     1
## 1059               campanulata     1
## 1060                 camphora*     1
## 1061                   Carabus     1
## 1062                  Caragana     1
## 1063                   Carduus     1
## 1064                    Carica     1
## 1065                   Caryota     1
## 1066                   catappa     1
## 1067                     ceiba     1
## 1068               Ceratinella     1
## 1069                 Ceratodon     1
## 1070                  Cerceris     1
## 1071              Chaenorhinum     1
## 1072             Chaenorrhinum     1
## 1073             Chaerophyllum     1
## 1074                 Chalybion     1
## 1075                   Chelone     1
## 1076                Chionodoxa     1
## 1077                Chondrilla     1
## 1078                  Cicurina     1
## 1079                     Cinn.     1
## 1080                    Citrus     1
## 1081                  Clausena     1
## 1082                 Clauzadea     1
## 1083                   Clivina     1
## 1084            Coccothraustes     1
## 1085                     Cocos     1
## 1086                Coelioxys      1
## 1087               Coenogonium     1
## 1088                    Coleus     1
## 1089                   confusa     1
## 1090                    Conium     1
## 1091               Convallaria     1
## 1092              Corynephorus     1
## 1093               Crabroninae     1
## 1094                   Crateva     1
## 1095                 Crocosmia     1
## 1096                    Crocus     1
## 1097               Crossocerus     1
## 1098                    cumini     1
## 1099            cunninghamiana     1
## 1100              cunninghamii     1
## 1101                 Cupressus     1
## 1102                     Cycas     1
## 1103                   Cynodon     1
## 1104               Cystopteris     1
## 1105                Delphinium     1
## 1106                  denudata     1
## 1107               Descurainia     1
## 1108                 Desmodium     1
## 1109                  Dicentra     1
## 1110                 Didymodon     1
## 1111                 Diervilla     1
## 1112                Dimocarpus     1
## 1113                Diplostyla     1
## 1114                  Dipsacus     1
## 1115              Doellingeria     1
## 1116            Dolichovespula     1
## 1117                     Draba     1
## 1118             Dracontomelon     1
## 1119               duperreanum     1
## 1120                    Dypsis     1
## 1121                Dyschirius     1
## 1122                   Dysdera     1
## 1123              Echinocystis     1
## 1124                  Echinops     1
## 1125                 Ectemnius     1
## 1126                 Elaeagnus     1
## 1127               Elaeocarpus     1
## 1128                  Elaphrus     1
## 1129                  elastica     1
## 1130                 elliottii     1
## 1131                    Elymus     1
## 1132                 Empidonax     1
## 1133                Entelecara     1
## 1134                  Episinus     1
## 1135             equisetifolia     1
## 1136                  Eranthis     1
## 1137                 Eratigena     1
## 1138                Erigonella     1
## 1139                       Ero     1
## 1140                  Eryngium     1
## 1141                 Estimated     1
## 1142                   Eumenes     1
## 1143                Euodynerus     1
## 1144                  Euonymus     1
## 1145                  Euophrys     1
## 1146               Eurhynchium     1
## 1147                  Euryopis     1
## 1148                Eutrochium     1
## 1149                  Exoneura     1
## 1150                     Fagus     1
## 1151                   Ficaria     1
## 1152                    Filago     1
## 1153                  Floronia     1
## 1154                  funebris     1
## 1155                Gaillardia     1
## 1156                  Garrulus     1
## 1157                glutinosa*     1
## 1158             Glyptostrobus     1
## 1159              Gnathonarium     1
## 1160                 Gomphrena     1
## 1161                  Gonatium     1
## 1162               Gongylidium     1
## 1163                   Gorytes     1
## 1164                  granatum     1
## 1165               grandiflora     1
## 1166                  Graphium     1
## 1167                   Grimmia     1
## 1168                   guajava     1
## 1169                Gypsophila     1
## 1170               hainanensis     1
## 1171              Haplodrassus     1
## 1172                 Harpactea     1
## 1173                  Helenium     1
## 1174                 Heliopsis     1
## 1175              heptaphylla*     1
## 1176                 Heracleum     1
## 1177              heterophylla     1
## 1178            heterophyllum*     1
## 1179             heterophyllus     1
## 1180                Homalictus     1
## 1181             Homalothecium     1
## 1182                Hyacinthus     1
## 1183              Hyperphyscia     1
## 1184              Hypocenomyce     1
## 1185                Hypogymnia     1
## 1186                  Hyssopus     1
## 1187                    indica     1
## 1188                    jambos     1
## 1189                  japonica     1
## 1190                 javanica*     1
## 1191                 Juniperus     1
## 1192                   Knautia     1
## 1193                   lansium     1
## 1194                  Lavatera     1
## 1195                   Lecidea     1
## 1196                  Leimonis     1
## 1197                   Leistus     1
## 1198             Lepthyphantes     1
## 1199                   Lestica     1
## 1200                   Licinus     1
## 1201                 Ligularia     1
## 1202                 Liocranum     1
## 1203                    Litchi     1
## 1204                    Litsea     1
## 1205                    longan     1
## 1206                 lutescens     1
## 1207                   Lycopus     1
## 1208                 Macaranga     1
## 1209             macrophyllus*     1
## 1210          madagascariensis     1
## 1211                   Mahonia     1
## 1212                 Mangifera     1
## 1213                   mangium     1
## 1214                 Manilkara     1
## 1215               massoniana*     1
## 1216                Matteuccia     1
## 1217                  Michelia     1
## 1218                 Micrargus     1
## 1219               microcarpa*     1
## 1220                 Microneta     1
## 1221                Milleriana     1
## 1222                 Mniotilta     1
## 1223                Moehringia     1
## 1224                 moluccana     1
## 1225                   Monobia     1
## 1226                 Motacilla     1
## 1227                 Muscicapa     1
## 1228                 Myrmecina     1
## 1229                 Neottiura     1
## 1230                   Neriene     1
## 1231                 Nicotiana     1
## 1232 nitidus ssp. lingnanensis     1
## 1233                  nucifera     1
## 1234                  Odiellus     1
## 1235                 Odontites     1
## 1236                  oleander     1
## 1237                    Ononis     1
## 1238              Ornithogalum     1
## 1239                    Osmia      1
## 1240                  Oxybelus     1
## 1241            Palliduphantes     1
## 1242                    papaya     1
## 1243                   Pardosa     1
## 1244                  Parmelia     1
## 1245               Passaloecus     1
## 1246                 Pastinaca     1
## 1247                 Paulownia     1
## 1248                Pelecopsis     1
## 1249                Pemphredon     1
## 1250                  pensilis     1
## 1251                Peponapis      1
## 1252                    Persea     1
## 1253               Petrorhagia     1
## 1254                 Phaseolus     1
## 1255                  Phedimus     1
## 1256              Philadelphus     1
## 1257                    Phleum     1
## 1258                  Phlyctis     1
## 1259                   Pholcus     1
## 1260              Phrurolithus     1
## 1261               Physostegia     1
## 1262                     Picea     1
## 1263                     Picus     1
## 1264                Pimpinella     1
## 1265                  pinnata*     1
## 1266                    Pipilo     1
## 1267               Pittosporum     1
## 1268               Plagiomnium     1
## 1269                  Plumeria     1
## 1270                Podocarpus     1
## 1271                  Polistes     1
## 1272                Polycarpon     1
## 1273               Polygonatum     1
## 1274                 Polyscias     1
## 1275               Polytrichum     1
## 1276                    Ponera     1
## 1277                  Pongamia     1
## 1278                    Porina     1
## 1279                  Porpidia     1
## 1280               Prinerigone     1
## 1281                  Psenulus     1
## 1282              Pseudevernia     1
## 1283               Pseudotsuga     1
## 1284                   Psidium     1
## 1285               Psilolechia     1
## 1286              Pterospermum     1
## 1287                Pulsatilla     1
## 1288                    Punica     1
## 1289                Pyracantha     1
## 1290                  Ramalina     1
## 1291                  Ravenala     1
## 1292                  revoluta     1
## 1293                Reynoutria     1
## 1294            Rhynchostegium     1
## 1295                   Rilaena     1
## 1296                  Robertus     1
## 1297                   robusta     1
## 1298                roebelenii     1
## 1299             romanzoffiana     1
## 1300                 Roystonea     1
## 1301                     rubra     1
## 1302                 Sarcogyne     1
## 1303                  Satureja     1
## 1304                 Satyrinae     1
## 1305                  Scaevola     1
## 1306                Sceliphron     1
## 1307                Schefflera     1
## 1308                    Scilla     1
## 1309                    Scolia     1
## 1310            Scoliciosporum     1
## 1311                  Scolopax     1
## 1312            Scorzoneroides     1
## 1313                 Segestria     1
## 1314                     Senna     1
## 1315                 sinensis*     1
## 1316                     Sitta     1
## 1317                       sp.     1
## 1318                 Spathodea     1
## 1319                  Sphecius     1
## 1320                  squamosa     1
## 1321            Stemonyphantes     1
## 1322              Stereocaulon     1
## 1323                     Stipa     1
## 1324               surattensis     1
## 1325                   Syagrus     1
## 1326                Symmorphus     1
## 1327            Symphoricarpos     1
## 1328                 Syncarpia     1
## 1329                  Tachytes     1
## 1330   tanarius var. tomentosa     1
## 1331                Terminalia     1
## 1332               Tetragonula     1
## 1333                Thalictrum     1
## 1334                   Thyreus     1
## 1335                 Toxomerus     1
## 1336                tripinnata     1
## 1337                  Trochosa     1
## 1338                  Trogulus     1
## 1339                Tropaeolum     1
## 1340                Troxochrus     1
## 1341                Trypoxylon     1
## 1342                     Tsuga     1
## 1343                    Tulipa     1
## 1344              unilocularis     1
## 1345                 Valeriana     1
## 1346                   Vezdaea     1
## 1347                 viminalis     1
## 1348                     Vitex     1
## 1349                    Vulpia     1
## 1350                 Vulpicida     1
## 1351                 Xylocopa      1
## 1352                  Xysticus     1
## 1353                   Yulania     1
## 1354                    zapota     1
## 1355                  Zodarion     1
## 1356                      Zora     1
spp.nbird <- meta %>% filter(Taxa.simplified!="birds") %>%  group_by(Genus) %>% summarize(n=length(Species)) %>% arrange(-n) %>% data.frame() %>% head()
spp.nbird
##          Genus     n
## 1              17209
## 2      Vanessa   699
## 3      Andrena   696
## 4       Bombus   555
## 5       Pieris   515
## 6 Lasioglossum   440
## Appendix Figures

meta <- read.csv("data//Master.GI.Datasets.csv")
## Omit repo 3 because duplicated with study 1305 and remove repo-9 because not equivalent GI comparisons. Removed Repo 3 because compare roof with ground
meta <- meta %>% filter(Study != "repo.3" & Study!="repo.9" & Study!="repo.1") 

## Drop relative abundance because difference = 0 
meta <- meta %>% filter(Estimate!="Relative.Abundance")

## pH

ph.count <- subset(meta, pH>0 & Genus != "")

ggplot(ph.count) + geom_density(aes(pH, fill=Genus), position="stack") + xlab("pH of retention pond") + ylab("frequency of occurrence")+theme_set(theme_bw(base_size = 22))+theme_bw()

se <- function(x) {sd(x)/sqrt(length(x))}

## Depth
depth <- subset(meta, depth..m.>0 )
depth <- depth %>% group_by(depth..m.) %>% summarize(avg=mean(Value), error=se(Value))

ggplot(depth, aes(x=depth..m., y=avg)) + geom_point( size=4) + geom_errorbar(data=depth, aes(ymin=avg-error, ymax=avg+error), width=0.03)+ xlab("depth of retention pond (m)") + ylab("average number of individuals observed")+theme_set(theme_bw(base_size = 22))+theme_bw()

## Height
high <- subset(meta, GI.height..m.>0 & Stat=="mean")
high <- filter(high, Estimate %in% c("abundance","richness"))
high <- high %>% group_by(GI.height..m.,Estimate) %>% summarize(Value=mean(Value))

ggplot(high) + geom_point(aes(x=GI.height..m., y=Value)) + facet_grid(~Estimate)+ xlab("height of green roof (m)") + ylab("average number observed")+theme_set(theme_bw(base_size = 22))+theme_bw()